TieIncred
/

verizon_model1

@@ -15,11 +15,11 @@ should probably proofread and complete it, then remove this comment. -->
 # verizon_model1
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0752
-- Accuracy: 0.9804
-- F1: 0.9797
 ## Model description
@@ -50,26 +50,26 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 1.5222        | 1.0   | 8    | 1.4173          | 0.5686   | 0.5681 |
-| 1.2748        | 2.0   | 16   | 1.1744          | 0.7647   | 0.6850 |
-| 1.0552        | 3.0   | 24   | 0.9130          | 0.7843   | 0.7001 |
-| 0.8588        | 4.0   | 32   | 0.6877          | 0.8824   | 0.8290 |
-| 0.6473        | 5.0   | 40   | 0.5120          | 0.8824   | 0.8291 |
-| 0.5048        | 6.0   | 48   | 0.3791          | 0.9216   | 0.9049 |
-| 0.3041        | 7.0   | 56   | 0.2843          | 0.9804   | 0.9797 |
-| 0.2355        | 8.0   | 64   | 0.2135          | 0.9804   | 0.9797 |
-| 0.2168        | 9.0   | 72   | 0.1657          | 0.9804   | 0.9797 |
-| 0.1318        | 10.0  | 80   | 0.1408          | 0.9804   | 0.9797 |
-| 0.1205        | 11.0  | 88   | 0.1167          | 0.9804   | 0.9797 |
-| 0.0858        | 12.0  | 96   | 0.1037          | 0.9804   | 0.9797 |
-| 0.0968        | 13.0  | 104  | 0.0954          | 0.9804   | 0.9797 |
-| 0.0658        | 14.0  | 112  | 0.0894          | 0.9804   | 0.9797 |
-| 0.0655        | 15.0  | 120  | 0.0828          | 0.9804   | 0.9797 |
-| 0.0581        | 16.0  | 128  | 0.0794          | 0.9804   | 0.9797 |
-| 0.0612        | 17.0  | 136  | 0.0786          | 0.9804   | 0.9797 |
-| 0.059         | 18.0  | 144  | 0.0767          | 0.9804   | 0.9797 |
-| 0.0512        | 19.0  | 152  | 0.0756          | 0.9804   | 0.9797 |
-| 0.0479        | 20.0  | 160  | 0.0752          | 0.9804   | 0.9797 |
 ### Framework versions

 # verizon_model1
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.0242
+- Accuracy: 1.0
+- F1: 1.0
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 1.458         | 1.0   | 8    | 1.1774          | 0.7451   | 0.6817 |
+| 1.1574        | 2.0   | 16   | 0.8376          | 0.7843   | 0.6934 |
+| 0.8281        | 3.0   | 24   | 0.6155          | 0.8627   | 0.8055 |
+| 0.6272        | 4.0   | 32   | 0.4462          | 0.8824   | 0.8493 |
+| 0.4532        | 5.0   | 40   | 0.3344          | 0.9216   | 0.9111 |
+| 0.3607        | 6.0   | 48   | 0.2535          | 1.0      | 1.0    |
+| 0.2153        | 7.0   | 56   | 0.1961          | 0.9804   | 0.9800 |
+| 0.1704        | 8.0   | 64   | 0.1489          | 1.0      | 1.0    |
+| 0.1238        | 9.0   | 72   | 0.1116          | 1.0      | 1.0    |
+| 0.0998        | 10.0  | 80   | 0.0841          | 1.0      | 1.0    |
+| 0.097         | 11.0  | 88   | 0.0642          | 1.0      | 1.0    |
+| 0.0751        | 12.0  | 96   | 0.0510          | 1.0      | 1.0    |
+| 0.0583        | 13.0  | 104  | 0.0421          | 1.0      | 1.0    |
+| 0.0422        | 14.0  | 112  | 0.0350          | 1.0      | 1.0    |
+| 0.037         | 15.0  | 120  | 0.0307          | 1.0      | 1.0    |
+| 0.0354        | 16.0  | 128  | 0.0282          | 1.0      | 1.0    |
+| 0.0336        | 17.0  | 136  | 0.0265          | 1.0      | 1.0    |
+| 0.0316        | 18.0  | 144  | 0.0252          | 1.0      | 1.0    |
+| 0.0341        | 19.0  | 152  | 0.0244          | 1.0      | 1.0    |
+| 0.027         | 20.0  | 160  | 0.0242          | 1.0      | 1.0    |
 ### Framework versions